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Bot Log Mining: Using Logs from Robotic Process Automation for Process Mining

: Egger, A.; Hofstede, A.H.M. ter; Kratsch, W.; Leemans, S.J.J.; Röglinger, M.; Wynn, M.T.


Dobbie, G.:
Conceptual Modeling. 39th International Conference, ER 2020. Proceedings : Vienna, Austria, November 3-6, 2020
Cham: Springer Nature, 2020 (Lecture Notes in Computer Science 12400)
ISBN: 978-3-030-62521-4 (Print)
ISBN: 978-3-030-62522-1 (Online)
ISBN: 978-3-030-62523-8
International Conference on Conceptual Modeling (ER) <39, 2020, Online>
Fraunhofer FIT ()

Robotic Process Automation (RPA) is an emerging technology for automating tasks using bots that can mimic human actions on computer systems. Most existing research focuses on the earlier phases of RPA implementations, e.g. the discovery of tasks that are suitable for automation. To detect exceptions and explore opportunities for bot and process redesign, historical data from RPA-enabled processes in the form of bot logs or process logs can be utilized. However, the isolated use of bot logs or process logs provides only limited insights and not a good understanding of an overall process. Therefore, we develop an approach that merges bot logs with process logs for process mining. A merged log enables an integrated view on the role and effects of bots in an RPA-enabled process. We first develop an integrated data model describing the structure and relation of bots and business processes. We then specify and instantiate a ‘bot log parser’ translating bot logs of three leading RPA vendors into the XES format. Further, we develop the ‘log merger’ functionality that merges bot logs with logs of the underlying business processes. We further introduce process mining measures allowing the analysis of a merged log.